The long-term objective of this proposal is to understand the perception of multiple abnormalities in an imaging examination and to develop strategies for improved diagnostic accuracy and patient outcome. We are one of the few laboratories in the world pursuing the goal of reducing detection errors through a better understanding of the underlying perceptual processes involved. Failure to detect an abnormality is the most common class of error in diagnostic imaging and generally is considered the most serious by the medical community. Many of these errors have been attributed to "satisfaction of search", which occurs when a lesion is not reported because discovery of another abnormality has "satisfied" the goal of the search. Although we have gained some understanding of the mechanisms of satisfaction of search (SOS), there are significant questions that remain. Computed tomography (CT) may replace radiography as the most common radiology examination. CT produces a large number of images that can be displayed in many formats. The volume of data to be inspected may quickly overwhelm the radiologists' perceptual resources, creating increased risk of satisfaction of search error. Until recently, there had been no experimental studies of SOS error in the advanced imaging. Our first studies in CT demonstrated limited SOS effects, but further experiments are needed before we can safely conclude that SOS is not a major problem for CT imaging. Currently, there are few interventions to remedy SOS error. Innovative reporting methods and direction from diagnostic questions may hold promise. A voice-prompted checklist may prevent the radiologist from neglecting some crucial structure without requiring them to take their eyes off of the image. Clinical history prompts certain abnormalities, protects the radiologist from missing them even when other abnormalities are present. However, the prompts may increase SOS errors for unprompted abnormalities. We propose four definitive experiments to approach the complex questions that remain. The research methods will include analysis of receiver operating characteristic curves, the time course of detection responses and the observer's navigation and exploration through the CT image data array. The knowledge gained from this programmatic research will lead to reduction of observer error. Newer imaging methods such as computed tomography play an increasingly prominent role in diagnostic radiology. Although CT makes smaller and subtler lesions visible, finding them requires inspection of many more images. The sheer number of images in a modern radiology study can stretch the attention of the radiologist and lead to errors. This project pursues methods to reduce diagnostic errors through a better understanding of the underlying perceptual processes. [unreadable] [unreadable] [unreadable]